Fractional dynamics and MDS visualization of earthquake phenomena

This paper analyses earthquake data in the perspective of dynamical systems and fractional calculus (FC). This new standpoint uses Multidimensional Scaling (MDS) as a powerful clustering and visualization tool. FC extends the concepts of integrals and derivatives to non-integer and complex orders. MDS is a technique that produces spatial or geometric representations of complex objects, such that those objects that are perceived to be similar in some sense are placed on the MDS maps forming clusters. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analysed. The events are characterized by their magnitude and spatiotemporal distributions and are divided into fifty groups, according to the Flinn–Engdahl (F–E) seismic regions of Earth. Several correlation indices are proposed to quantify the similarities among regions. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools for understanding the global behaviour of earthquakes.

In permanent transit: discourses and maps of the intercultural experience

Instituto Politécnico do Porto. Instituto Superior de Contabilidade e Administração do Porto

Analysis and visualization of seismic data using mutual information

Seismic data is difficult to analyze and classical mathematical tools reveal strong limitations in exposing hidden relationships between earthquakes. In this paper, we study earthquake phenomena in the perspective of complex systems. Global seismic data, covering the period from 1962 up to 2011 is analyzed. The events, characterized by their magnitude, geographic location and time of occurrence, are divided into groups, either according to the Flinn-Engdahl (F-E) seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Two methods of analysis are considered and compared in this study. In a first method, the distributions of magnitudes are approximated by Gutenberg-Richter (G-R) distributions and the parameters used to reveal the relationships among regions. In the second method, the mutual information is calculated and adopted as a measure of similarity between regions. In both cases, using clustering analysis, visualization maps are generated, providing an intuitive and useful representation of the complex relationships that are present among seismic data. Such relationships might not be perceived on classical geographic maps. Therefore, the generated charts are a valid alternative to other visualization tools, for understanding the global behavior of earthquakes.

Effects of emotional valence and three-dimensionality of visual stimuli on brain activation: an fMRI study

BACKGROUND: Examining changes in brain activation linked with emotion-inducing stimuli is essential to the study of emotions. Due to the ecological potential of techniques such as virtual reality (VR), inspection of whether brain activation in response to emotional stimuli can be modulated by the three-dimensional (3D) properties of the images is important. OBJECTIVE: The current study sought to test whether the activation of brain areas involved in the emotional processing of scenarios of different valences can be modulated by 3D. Therefore, the focus was made on the interaction effect between emotion-inducing stimuli of different emotional valences (pleasant, unpleasant and neutral valences) and visualization types (2D, 3D). However, main effects were also analyzed.METHODS: The effect of emotional valence and visualization types and their interaction were analyzed through a 3x2 repeated measures ANOVA. Post-hoc t-tests were performed under a ROI-analysis approach. RESULTS: The results show increased brain activation for the 3D affective-inducing stimuli in comparison with the same stimuli in 2D scenarios, mostly in cortical and subcortical regions that are related to emotional processing, in addition to visual processing regions. CONCLUSIONS: This study has the potential of clarify brain mechanisms involved in the processing of emotional stimuli (scenarios’ valence) and their interaction with three-dimensionality.

Analysis of temperature time-series: embedding dynamics into the MDS method

Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.

Multidimensional scaling visualization of earthquake phenomena

Earthquakes are associated with negative events, such as large number of casualties, destruction of buildings and infrastructures, or emergence of tsunamis. In this paper, we apply the Multidimensional Scaling (MDS) analysis to earthquake data. MDS is a set of techniques that produce spatial or geometric representations of complex objects, such that, objects perceived to be similar/distinct in some sense are placed nearby/distant on the MDS maps. The interpretation of the charts is based on the resulting clusters since MDS produces a different locus for each similarity measure. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analyzed. The events, characterized by their magnitude and spatiotemporal distributions, are divided into groups, either according to the Flinn–Engdahl seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Space-time and Space-frequency correlation indices are proposed to quantify the similarities among events. MDS has the advantage of avoiding sensitivity to the non-uniform spatial distribution of seismic data, resulting from poorly instrumented areas, and is well suited for accessing dynamics of complex systems. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools, for understanding the global behavior of earthquakes.

Trade-Off Performance Regions of Slotted ALOHA Protocol using Multi-Objective Optimization

10th Conference on Telecommunications (Conftele 2015), Aveiro, Portugal.

Post-MAPS: An interactive acquisition platform for gastroenterology

Post-MAPS is a web platform that collects gastroenterological exam data from several european hospital centers, to be used in future clinical studies and was developed in partnership with experts from the gastroenterological area and information technology (IT) technicians. However, although functional, this platform has some issues that are crucial for its functioning, and can render user interaction unpleasant and exhaustive. Accordingly, we proposed the development of a new web platform, in which we aimed for an improvement in terms of usability, data uni cation and interoperability. Therefore, it was necessary to identify and study different ways of acquiring clinical data and review some of the existing clinical databases in order to understand how they work and what type of data they store, as well as their impact and contribution to clinical knowledge. Closely linked to the data model is the ability to share data with other systems, so, we also studied the concept of interoperability and analyzed some of the most widely used international standards, such as DICOM, HL7 and openEHR. As one of the primary objectives of this project was to achieve a better level of usability, practices related to Human Computer-Interaction, such as requirement analysis, creation of conceptual models, prototyping, and evaluation were also studied. Before we began the development, we conducted an analysis of the previous platform, from a functional point of view, which allowed us to gather not only a list of architectural and interface issues, but also a list of improvement opportunities. It was also performed a small preliminary study in order to evaluate the platform's usability, where we were able to realize that perceived usability is different between users, and that, in some aspects, varies according to their location, age and years of experience. Based on the information gathered during the platform's analysis and in the conclusions of the preliminary study, a new platform was developed, prepared for all potential users, from the inexperienced to the most comfortable with technology. It presents major improvements in terms of usability, also providing several new features that simplify the users' work, improving their interaction with the system, making their experience more enjoyable.